Github user mengxr commented on a diff in the pull request:
https://github.com/apache/spark/pull/3833#discussion_r23824003
--- Diff:
mllib/src/main/scala/org/apache/spark/mllib/regression/GeneralizedLinearAlgorithm.scala
---
@@ -228,7 +274,34 @@ abstract class GeneralizedLinearAlgorithm[M <:
GeneralizedLinearModel]
* is the coefficient in the original space, and v_i is the variance
of the column i.
*/
if (useFeatureScaling) {
- weights = scaler.transform(weights)
+ if (numOfLinearPredictor == 1) {
+ weights = scaler.transform(weights)
+ } else {
+ /**
+ * For `numOfLinearPredictor > 1`, we have to transform the
weights back to the original
+ * scale for each set of linear predictor. Note that the
intercepts have to be explicitly
+ * excluded when `addIntercept == true` since the intercepts are
part of weights now.
+ */
+ var i = 0
+ val weightsArray = weights.toArray
+ while (i < numOfLinearPredictor) {
+ val start = i * (weights.size / numOfLinearPredictor)
+ val end = (i + 1) * (weights.size / numOfLinearPredictor) - { if
(addIntercept) 1 else 0 }
+
+ val partialWeightsArray = scaler.transform(
+ Vectors.dense(weightsArray.slice(start, end))).toArray
+
+ var j = start
+ var k = 0
+ while (j < end) {
+ weightsArray(j) = partialWeightsArray(k)
--- End diff --
`System.arraycopy`
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